Pyser Testing

When Will the Evidence From Florida and Texas Break Through the SAGE Groupthink?

The latest model of doom from Government advisory group SAGE appeared yesterday, predicting a ludicrous 10,000 hospital admissions a day in mid-July in a vaccinated population (nearly three times the January peak) because of the Indian variant – and that’s the central scenario. Furthermore, the researchers don’t even think the Indian variant is more deadly or particularly good at evading vaccines. So how do they conclude it will precipitate such a calamity?

Professor Adam Kucharski, a SAGE modeller from the London School of Hygiene and Tropical Medicine (LSHTM), explains their reasoning:

The issue is that many people have a mental image that we’ve [already] had the biggest possible epidemic waves, whereas we’ve actually had ones that are relatively small compared to what could have happened without control measures in place. Because of these controls, only a fraction of the people who could have got infected in the past year or so have been infected, so they’re still out there. Of course, for many of these people vaccines have now decreased their risk substantially. But a very large number of infections that come with a very small individual level of risk can produce a similar outcome to a smaller epidemic that carries a larger individual level of risk.

Maths whizz Glen Bishop, writing for Lockdown Sceptics, has shown why SAGE’s assumptions are so unrealistic as to produce these highly implausible scenarios. In their central scenario, for example, their assumptions imply that up to half of the UK will be simultaneously infected in one week in mid-July. This is despite the January peak only having around 2% of the population infected at one time, according to the ONS.

Another of the models’ big assumptions, prominent in what Prof Kucharski says above, is that lockdowns and social distancing have successfully suppressed the virus and that it is only because they continue in some form that the flood of infections, hospitalisations and deaths is held back. The latest modelling starkly shows how, even with a high vaccination coverage as in the UK, such an assumption can produce predictions so dire they send twitchy Governments reaching for the lockdown order.

As the SAGE briefing says:

At this point in the vaccine rollout, there are still too few adults vaccinated to prevent a significant resurgence that ultimately could put unsustainable pressure on the NHS, without non-pharmaceutical interventions. … It is a realistic possibility that this new variant of concern could be 50% more transmissible. If [the Indian variant] does have such a large transmission advantage, it is a realistic possibility that progressing with all roadmap steps would lead to a substantial resurgence of hospitalisations.

In fact, there is no evidence (outside models, which are not evidence) that lockdown measures or social distancing have any significant impact on reducing Covid infections or deaths. This is why the states in America which removed their restrictions in March (Texas) or last autumn (Florida) or never imposed them (South Dakota) are doing no worse, and often better, than many states which maintained strict restrictions throughout the winter (see the graph above). Sweden demonstrates a similar point in Europe.

The depressing truth, though, is that sceptics have largely failed to get this basic point across to those in charge and their scientific advisers. It’s not as though the evidence is not there. There are numerous peer-reviewed articles in leading journals that set out the evidence on this, and more keep appearing. Leading scientists have raised their heads to make the evidence-based case.

Graphs like the above, which should by themselves undermine the entire lockdown edifice, are easy to produce. Leading journalists such as Fraser Nelson, writing in one of the leading Tory newspapers, the Telegraph, has pointed repeatedly to the evidence on this. The data is plain for all to see and the voices highlighting it are not marginal or lacking in credibility.

Yet here we are again, with another model built on dubious assumptions and a presumption of lockdown efficacy once more imperilling our liberty. Freedom has never felt so fragile as in these past 14 months, when access to basic liberties has rested on the evidence-free assumptions made by a small group of mathematical modellers whose word seems to be taken as holy writ by those in charge.

Adam Kucharski is on Twitter. So why not ask him (politely!) why, if so many people remain so susceptible to this virus and its variants as to produce such dire predictions, Florida, Texas and South Dakota have fared no worse than places which have imposed or maintained restrictions? I’ve put the graph as the featured image to make it easy to share – just put a link to this article in the tweet and the graph should appear. If you get any answers from him, why not email them to us here.

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